| Title | An evolutionary approach for congestion prediction on IoT data streams in smart city environment |
|---|---|
| ID_Doc | 41668 |
| Authors | Mishra, S; Shibu, A; Balan, R; Hota, C |
| Title | An evolutionary approach for congestion prediction on IoT data streams in smart city environment |
| Year | 2020 |
| Published | |
| Abstract | This work intends to predict traffic congestions from high-speed IoT data streams using Complex Event Processing (CEP) engines. As CEP engines are reactive in nature and have static thresholds, we propose an unsupervised Genetic Algorithm based clustering procedure which classifies the traffic into congestion and no-congestion classes. It also enables the CEP rule engine to form complex events with adaptive thresholds which change with context. Extensive analysis of traffic features is implemented so as to identify the relationship between temporal, environmental and social features and their impact on the CEP rule formation. A high recall of 96.8% indicates better performance, with lesser false positives, over baseline, and multiple hypothesis test results further, strengthen the effectiveness of the proposed approach. |
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